Nishant A. Mehta

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Alexander GrayIBM Research AIVerified email at cc.gatech.edu
Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden UniversityVerified email at cwi.nl
Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Parikshit RamIBM ResearchVerified email at ibm.com
William B. MarchApple, Inc.Verified email at apple.com
Ryan R. CurtinFree agentVerified email at ratml.org
Bingshan HuData Science Institute at University of British ColumbiaVerified email at cs.ubc.ca
Mark D. ReidAppleVerified email at reid.name
Tim van ErvenAssociate professor at the University of Amsterdam, the NetherlandsVerified email at uva.nl
Zhiming HuangUniversity of VictoriaVerified email at uvic.ca
Melody Moore JacksonProfessor of Computer Science, Georgia TechVerified email at cc.gatech.edu
Rafael FrongilloComputer Science, CU BoulderVerified email at colorado.edu
Jianping PanUniversity of VictoriaVerified email at uvic.ca
Dongryeol LeeResearch IndustryVerified email at saintpeters.edu
Jacqueline FairleySenior Research Engineer, Georgia Tech Research InstituteVerified email at gtri.gatech.edu
Donald L. BliwiseProfessor of Neurology, Emory University School of MedicineVerified email at emory.edu
George GeorgoulasPost Doc researcherVerified email at datawise.ai
Rianne de HeideAssistant professor, Mathematics department, Vrije Universiteit AmsterdamVerified email at utwente.nl
Thad StarnerProfessor of Computing, Georgia Institute of TechnologyVerified email at cc.gatech.edu
Quan NguyenUniversity of VictoriaVerified email at uvic.ca

Nishant A. Mehta

Assistant Professor, University of Victoria

Verified email at uvic.ca - Homepage

machine learning learning theory statistical learning theory luckiness


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MLPACK: A scalable C++ machine learning library RR Curtin, JR Cline, NP Slagle, WB March, P Ram, NA Mehta, AG Gray The Journal of Machine Learning Research 14 (1), 801-805, 2013	219	2013
Fast rates in statistical and online learning T Van Erven, P Grunwald, NA Mehta, M Reid, R Williamson MIT Press, 2015	118	2015
Fast rates for general unbounded loss functions: from ERM to generalized Bayes PD Grünwald, NA Mehta Journal of Machine Learning Research 21 (56), 1-80, 2020	108	2020
Fast rates with high probability in exp-concave statistical learning N Mehta Artificial Intelligence and Statistics, 1085-1093, 2017	50	2017
Sparsity-based generalization bounds for predictive sparse coding N Mehta, A Gray International Conference on Machine Learning, 36-44, 2013	47	2013
A tight excess risk bound via a unified PAC-Bayesian–Rademacher–Shtarkov–MDL complexity PD Grünwald, NA Mehta Algorithmic Learning Theory, 433-465, 2019	37	2019
Safe-Bayesian generalized linear regression R Heide, A Kirichenko, P Grunwald, N Mehta International Conference on Artificial Intelligence and Statistics, 2623-2633, 2020	33	2020
On the sample complexity of predictive sparse coding NA Mehta, AG Gray arXiv preprint arXiv:1202.4050, 2012	22	2012
Generalized mixability via entropic duality MD Reid, RM Frongillo, RC Williamson, N Mehta Conference on Learning Theory, 1501-1522, 2015	19	2015
Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep JA Fairley, G Georgoulas, NA Mehta, AG Gray, DL Bliwise Biomedical Signal Processing and Control 7 (6), 606-615, 2012	19	2012
Independent component analysis F Westad, M Kermit Elsevier, 2009	18	2009
Fast rates with unbounded losses PD Grünwald, NA Mehta arXiv preprint arXiv:1605.00252 2, 14, 2016	17	2016
Modeling software behavior using learned predicates AX Zheng, MS Musuvathi, NA Mehta US Patent 9,098,621, 2015	17	2015
From stochastic mixability to fast rates NA Mehta, RC Williamson Advances in Neural Information Processing Systems 27, 2014	17	2014
Intelligent caching algorithms in heterogeneous wireless networks with uncertainty B Hu, Y Chen, Z Huang, NA Mehta, J Pan 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019	13	2019
Optimal algorithms for private online learning in a stochastic environment B Hu, Z Huang, NA Mehta arXiv preprint arXiv:2102.07929, 2021	11	2021
Problem-dependent regret bounds for online learning with feedback graphs B Hu, NA Mehta, J Pan Uncertainty in Artificial Intelligence, 852-861, 2020	11	2020
Minimax multi-task learning and a generalized loss-compositional paradigm for MTL N Mehta, D Lee, A Gray Advances in Neural Information Processing Systems 25, 2012	11	2012
Fast rates for general unbounded loss functions: from ERM to generalized Bayes PD Grünwald, NA Mehta arXiv preprint arXiv:1605.00252, 2016	8	2016
VisIRR: interactive visual information retrieval and recommendation for large-scale document data J Choo, C Lee, E Clarkson, Z Liu, H Lee, DHP Chau, F Li, R Kannan, ... Georgia Institute of Technology, 2013	8	2013

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